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  1. Life, Local Constraints and Meaning Generation. An Evolutionary Approach to Cognition (2015).Christophe Menant - manuscript
    The relations between life and cogntion have been addressed through different perspectives [Stewart 1996, Boden 2001, Bourgine and Stewart 2004, van Duijn & all 2006, Di Paolo 2009]. We would like here to address that subject by relating life to cognition through a process of meaning generation. Life emerged on earth as a far from thermodynamic equilibrium performance that had to maintain herself. Life is charactertized by a ‘stay alive’ constraint that has to be satisfied (such constraint can be included (...)
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  2. Chatting with Chat(GPT-4): Quid est Understanding?Elan Moritz - manuscript
    What is Understanding? This is the first of a series of Chats with OpenAI’s ChatGPT (Chat). The main goal is to obtain Chat’s response to a series of questions about the concept of ’understand- ing’. The approach is a conversational approach where the author (labeled as user) asks (prompts) Chat, obtains a response, and then uses the response to formulate followup questions. David Deutsch’s assertion of the primality of the process / capability of understanding is used as the starting point. (...)
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  3. Medical Image Classification with Machine Learning Classifier.Destiny Agboro - forthcoming - Journal of Computer Science.
    In contemporary healthcare, medical image categorization is essential for illness prediction, diagnosis, and therapy planning. The emergence of digital imaging technology has led to a significant increase in research into the use of machine learning (ML) techniques for the categorization of images in medical data. We provide a thorough summary of recent developments in this area in this review, using knowledge from the most recent research and cutting-edge methods.We begin by discussing the unique challenges and opportunities associated with medical image (...)
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  4. “Even an AI could do that”.Emanuele Arielli - forthcoming - Http://Manovich.Net/Index.Php/Projects/Artificial-Aesthetics.
    Chapter 1 of the ongoing online publication "Artificial Aesthetics: A Critical Guide to AI, Media and Design", Lev Manovich and Emanuele Arielli -/- Book information: Assume you're a designer, an architect, a photographer, a videographer, a curator, an art historian, a musician, a writer, an artist, or any other creative professional or student. Perhaps you're a digital content creator who works across multiple platforms. Alternatively, you could be an art historian, curator, or museum professional. -/- You may be wondering how (...)
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  5. Human Perception and The Artificial Gaze.Emanuele Arielli & Lev Manovich - forthcoming - In Emanuele Arielli & Lev Manovich (eds.), Artificial Aesthetics.
  6. Restful Web Services for Scalable Data Mining.Solar Cesc - forthcoming - International Journal of Research and Innovation in Applied Science.
    Scalability, efficiency, and security had been a persistent problem over the years in data mining, several techniques had been proposed and implemented but none had been able to solve the problem of scalability, efficiency and security from cloud computing. In this research, we solve the problem scalability, efficiency and security in data mining over cloud computing by using a restful web services and combination of different technologies and tools, our model was trained by using different machine learning algorithm, and finally (...)
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  7. Real Sparks of Artificial Intelligence and the Importance of Inner Interpretability.Alex Grzankowski - forthcoming - Inquiry: An Interdisciplinary Journal of Philosophy.
    The present paper looks at one of the most thorough articles on the intelligence of GPT, research conducted by engineers at Microsoft. Although there is a great deal of value in their work, I will argue that, for familiar philosophical reasons, their methodology, ‘Black-box Interpretability’ is wrongheaded. But there is a better way. There is an exciting and emerging discipline of ‘Inner Interpretability’ (also sometimes called ‘White-box Interpretability’) that aims to uncover the internal activations and weights of models in order (...)
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  8. Making AI Intelligible: Philosophical Foundations. By Herman Cappelen and Josh Dever. [REVIEW]Nikhil Mahant - forthcoming - Philosophical Quarterly.
    Linguistic outputs generated by modern machine-learning neural net AI systems seem to have the same contents—i.e., meaning, semantic value, etc.—as the corresponding human-generated utterances and texts. Building upon this essential premise, Herman Cappelen and Josh Dever's Making AI Intelligible sets for itself the task of addressing the question of how AI-generated outputs have the contents that they seem to have (henceforth, ‘the question of AI Content’). In pursuing this ambitious task, the book makes several high-level, framework observations about how a (...)
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  9. Understanding with Toy Surrogate Models in Machine Learning.Andrés Páez - forthcoming - Minds and Machines.
    In the natural and social sciences, it is common to use toy models—extremely simple and highly idealized representations—to understand complex phenomena. Some of the simple surrogate models used to understand opaque machine learning (ML) models, such as rule lists and sparse decision trees, bear some resemblance to scientific toy models. They allow non-experts to understand how an opaque ML model works globally via a much simpler model that highlights the most relevant features of the input space and their effect on (...)
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  10. Egocentric Bias and Doubt in Cognitive Agents.Nanda Kishore Sreenivas & Shrisha Rao - forthcoming - 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 2019.
    Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are susceptible to. This work presents a method to model egocentric bias, the real-life tendency to emphasize one's own opinion heavily when presented with multiple opinions. We use a symmetric distribution, centered at an agent's own opinion, as opposed to the Bounded Confidence (BC) model used in (...)
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  11. Understanding Moral Responsibility in Automated Decision-Making: Responsibility Gaps and Strategies to Address Them.Andrea Berber & Jelena Mijić - 2024 - Theoria: Beograd 67 (3):177-192.
    This paper delves into the use of machine learning-based systems in decision-making processes and its implications for moral responsibility as traditionally defined. It focuses on the emergence of responsibility gaps and examines proposed strategies to address them. The paper aims to provide an introductory and comprehensive overview of the ongoing debate surrounding moral responsibility in automated decision-making. By thoroughly examining these issues, we seek to contribute to a deeper understanding of the implications of AI integration in society.
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  12. The FHJ debate: Will artificial intelligence replace clinical decision-making within our lifetimes?Joshua Hatherley, Anne Kinderlerer, Jens Christian Bjerring, Lauritz Munch & Lynsey Threlfall - 2024 - Future Healthcare Journal 11 (3):100178.
  13. Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions.Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith & Simone Stumpf - 2024 - Information Fusion 106 (June 2024).
    As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from diverse (...)
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  14. Artificial Intelligence for the Internal Democracy of Political Parties.Claudio Novelli, Giuliano Formisano, Prathm Juneja, Sandri Giulia & Luciano Floridi - 2024 - Minds and Machines 34 (36):1-26.
    The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to partial data collection, rare updates, and significant resource demands. To address these issues, the article suggests that specific data management and Machine Learning techniques, such as natural language processing and sentiment analysis, can (...)
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  15. Artificial Intelligence in Intelligence Agencies, Defense and National Security.Nicolae Sfetcu - 2024 - Bucharest, Romania: MultiMedia Publishing.
    This book explores the use of artificial intelligence by intelligence services around the world and its critical role in intelligence analysis, defense, and national security. Intelligence services play a crucial role in national security, and the adoption of artificial intelligence technologies has had a significant impact on their operations. It also examines the various applications of artificial intelligence in intelligence services, the implications, challenges and ethical considerations associated with its use. The book emphasizes the need for continued research and development (...)
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  16. Războiul electronic și inteligența artificială.Nicolae Sfetcu - 2024 - Bucharest, Romania: MultiMedia Publishing.
    Războiul electronic este o componentă critică a operațiunilor militare moderne și a suferit progrese semnificative în ultimii ani. Această carte oferă o privire de ansamblu asupra războiului electronic, a dezvoltării sale istorice, a componentelor cheie și a rolului său în scenariile de conflict contemporane. De asemenea, se discută tendințele și provocările emergente în războiul electronic și și relevanța sa contemporană într-o eră a tehnologiei avansate și a amenințărilor cibernetice, subliniind necesitatea cercetării și dezvoltării continue în acest domeniu. Cartea explorează intersecția (...)
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  17. Paskian Algebra: A Discursive Approach to Conversational Multi-agent Systems.Thomas Manning - 2023 - Cybernetics and Human Knowing 30 (1-2):67-81.
    The purpose of this study is to compile a selection of the various formalisms found in conversation theory to introduce readers to Pask's discursive algebra. In this way, the text demonstrates how concept sharing and concept formation by means of the interaction of two participants may be formalized. The approach taken in this study is to examine the formal notation system used by Pask and demonstrate how such formalisms may be used to represent concept sharing and concept formation through conversation. (...)
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  18. What is conversation theory?Thomas Manning - 2023 - Cybernetics and Human Knowing 30 (1-2):45-63.
    The purpose of the following text is to give readers a general introduction to Gordon Pask’s conversation theory, which is considered here to be a cybernetic and epistemological account of concept-forming and concept-sharing through conversational discourse and practice. While Pask devoted three lengthy tomes to articulate the theory and its applications, I believe it is necessary to give readers who are interested in conversation theory a general introduction to what I believe are the key features of his work in this (...)
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  19. Any Sufficiently Transparent Magic….Damien P. Williams - 2023 - American Religion 5 (1): 104-110.
    Religious perspectives, myth, and magic are not merely evocative lenses by which to understand the work done by algorithms and "AI" in the present day- though they are indeed that. And they're not merely the historical underpinnings of the practices of technology in general and the dream of "AI" in particular- though they are that, too. Rather, these elements resonate and recur throughout the past and present practice of "AI" development-and those practices then act as new inputs, foundations, tinting lenses (...)
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  20. AI-aesthetics and the Anthropocentric Myth of Creativity.Emanuele Arielli & Lev Manovich - 2022 - NODES 1 (19-20).
    Since the beginning of the 21st century, technologies like neural networks, deep learning and “artificial intelligence” (AI) have gradually entered the artistic realm. We witness the development of systems that aim to assess, evaluate and appreciate artifacts according to artistic and aesthetic criteria or by observing people’s preferences. In addition to that, AI is now used to generate new synthetic artifacts. When a machine paints a Rembrandt, composes a Bach sonata, or completes a Beethoven symphony, we say that this is (...)
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  21. AI’s Role in Creative Processes: A Functionalist Approach.Leonardo Arriagada & Gabriela Arriagada-Bruneau - 2022 - Odradek. Studies in Philosophy of Literature, Aesthetics, and New Media Theories 8 (1):77-110.
    From 1950 onwards, the study of creativity has not stopped. Today, AI has revitalised debates on the subject. That is especially controversial in the artworld, as the 21st century already features AI-generated artworks. Without discussing issues about AI agency, this article argues for AI’s creativity. For this, we first present a new functionalist understanding of Margaret Boden’s definition of creativity. This is followed by an analysis of empirical evidence on anthropocentric barriers in the perception of AI’s creative capabilities, which is (...)
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  22. Extending the Is-ought Problem to Top-down Artificial Moral Agents.Robert James M. Boyles - 2022 - Symposion: Theoretical and Applied Inquiries in Philosophy and Social Sciences 9 (2):171–189.
    This paper further cashes out the notion that particular types of intelligent systems are susceptible to the is-ought problem, which espouses the thesis that no evaluative conclusions may be inferred from factual premises alone. Specifically, it focuses on top-down artificial moral agents, providing ancillary support to the view that these kinds of artifacts are not capable of producing genuine moral judgements. Such is the case given that machines built via the classical programming approach are always composed of two parts, namely: (...)
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  23. COVID-19 and Singularity: Can the Philippines Survive Another Existential Threat?Robert James M. Boyles, Mark Anthony Dacela, Tyrone Renzo Evangelista & Jon Carlos Rodriguez - 2022 - Asia-Pacific Social Science Review 22 (2):181–195.
    In general, existential threats are those that may potentially result in the extinction of the entire human species, if not significantly endanger its living population. Among the said threats include, but not limited to, pandemics and the impacts of a technological singularity. As regards pandemics, significant work has already been done on how to mitigate, if not prevent, the aftereffects of this type of disaster. For one, certain problem areas on how to properly manage pandemic responses have already been identified, (...)
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  24. Computing Machinery and Sexual Difference: The Sexed Presuppositions Underlying the Turing Test.Amy Kind - 2022 - In Keya Maitra & Jennifer McWeeny (eds.), Feminist Philosophy of Mind. New York, NY, United States of America: Oxford University Press, Usa.
    In his 1950 paper “Computing Machinery and Intelligence,” Alan Turing proposed that we can determine whether a machine thinks by considering whether it can win at a simple imitation game. A neutral questioner communicates with two different systems – one a machine and a human being – without knowing which is which. If after some reasonable amount of time the machine is able to fool the questioner into identifying it as the human, the machine wins the game, and we should (...)
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  25. ANNs and Unifying Explanations: Reply to Erasmus, Brunet, and Fisher.Yunus Prasetya - 2022 - Philosophy and Technology 35 (2):1-9.
    In a recent article, Erasmus, Brunet, and Fisher (2021) argue that Artificial Neural Networks (ANNs) are explainable. They survey four influential accounts of explanation: the Deductive-Nomological model, the Inductive-Statistical model, the Causal-Mechanical model, and the New-Mechanist model. They argue that, on each of these accounts, the features that make something an explanation is invariant with regard to the complexity of the explanans and the explanandum. Therefore, they conclude, the complexity of ANNs (and other Machine Learning models) does not make them (...)
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  26. Measuring Intelligence and Growth Rate: Variations on Hibbard's Intelligence Measure.Samuel Alexander & Bill Hibbard - 2021 - Journal of Artificial General Intelligence 12 (1):1-25.
    In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard’s idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second, one specific (somewhat arbitrary) method for measuring said growth rates. Whereas Hibbard’s intelligence measure is based on the latter growth-rate-measuring method, we survey other methods (...)
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  27. Making AI Intelligible: Philosophical Foundations.Herman Cappelen & Josh Dever - 2021 - New York, USA: Oxford University Press.
    Can humans and artificial intelligences share concepts and communicate? Making AI Intelligible shows that philosophical work on the metaphysics of meaning can help answer these questions. Herman Cappelen and Josh Dever use the externalist tradition in philosophy to create models of how AIs and humans can understand each other. In doing so, they illustrate ways in which that philosophical tradition can be improved. The questions addressed in the book are not only theoretically interesting, but the answers have pressing practical implications. (...)
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  28. Towards Knowledge-driven Distillation and Explanation of Black-box Models.Roberto Confalonieri, Guendalina Righetti, Pietro Galliani, Nicolas Toquard, Oliver Kutz & Daniele Porello - 2021 - In Roberto Confalonieri, Guendalina Righetti, Pietro Galliani, Nicolas Toquard, Oliver Kutz & Daniele Porello (eds.), Proceedings of the Workshop on Data meets Applied Ontologies in Explainable {AI} {(DAO-XAI} 2021) part of Bratislava Knowledge September {(BAKS} 2021), Bratislava, Slovakia, September 18th to 19th, 2021. CEUR 2998.
    We introduce and discuss a knowledge-driven distillation approach to explaining black-box models by means of two kinds of interpretable models. The first is perceptron (or threshold) connectives, which enrich knowledge representation languages such as Description Logics with linear operators that serve as a bridge between statistical learning and logical reasoning. The second is Trepan Reloaded, an ap- proach that builds post-hoc explanations of black-box classifiers in the form of decision trees enhanced by domain knowledge. Our aim is, firstly, to target (...)
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  29. Dynamic Tractable Reasoning: A Modular Approach to Belief Revision.Holger Andreas - 2020 - Cham, Schweiz: Springer.
    This book aims to lay bare the logical foundations of tractable reasoning. It draws on Marvin Minsky's seminal work on frames, which has been highly influential in computer science and, to a lesser extent, in cognitive science. Only very few people have explored ideas about frames in logic, which is why the investigation in this book breaks new ground. The apparent intractability of dynamic, inferential reasoning is an unsolved problem in both cognitive science and logic-oriented artificial intelligence. By means of (...)
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  30. Why Friendly AIs won’t be that Friendly: A Friendly Reply to Muehlhauser and Bostrom.Robert James M. Boyles & Jeremiah Joven Joaquin - 2020 - AI and Society 35 (2):505–507.
    In “Why We Need Friendly AI”, Luke Muehlhauser and Nick Bostrom propose that for our species to survive the impending rise of superintelligent AIs, we need to ensure that they would be human-friendly. This discussion note offers a more natural but bleaker outlook: that in the end, if these AIs do arise, they won’t be that friendly.
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  31. A Tale of Two Deficits: Causality and Care in Medical AI.Melvin Chen - 2020 - Philosophy and Technology 33 (2):245-267.
    In this paper, two central questions will be addressed: ought we to implement medical AI technology in the medical domain? If yes, how ought we to implement this technology? I will critically engage with three options that exist with respect to these central questions: the Neo-Luddite option, the Assistive option, and the Substitutive option. I will first address key objections on behalf of the Neo-Luddite option: the Objection from Bias, the Objection from Artificial Autonomy, the Objection from Status Quo, and (...)
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  32. DNAOS for KREMMS: A distributed platform for knowledge resource entitlement, modeling, management, and sharing.Andre Cusson - 2020 - Journal of Knowledge Structures and Systems 1 (1):117-133.
    This article is a knowledge technology case study of DNAOS, a distributed platform for Knowledge Resource Entitlement, Modeling, Management, and Sharing (KREMMS). Some historical aspects of its design, development, and release are briefly discussed, after which the DNAOS technology is commented upon from the specific viewpoint of KREMMS. At the core of this platform is the conception of knowledge as a natural phenomenon, which conception is reflected in the ontology of this technology: Fundamental knowledge structures and structuring principles, believed to (...)
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  33. Acquisition of Autonomy in Biotechnology and Artificial Intelligence.Philippe Gagnon, Mathieu Guillermin, Olivier Georgeon, Juan R. Vidal & Béatrice de Montera - 2020 - In S. Hashimoto N. Callaos (ed.), Proceedings of the 11th International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC 2020, Volume II. Winter Garden: International Institute for Informatics and Systemics. pp. 168-172.
    This presentation discusses a notion encountered across disciplines, and in different facets of human activity: autonomous activity. We engage it in an interdisciplinary way. We start by considering the reactions and behaviors of biological entities to biotechnological intervention. An attempt is made to characterize the degree of freedom of embryos & clones, which show openness to different outcomes when the epigenetic developmental landscape is factored in. We then consider the claim made in programming and artificial intelligence that automata could show (...)
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  34. Ethics, Prosperity, and Society: Moral Evaluation Using Virtue Ethics and Utilitarianism.Aditya Hegde, Vibhav Agarwal & Shrisha Rao - 2020 - 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020).
    Modelling ethics is critical to understanding and analysing social phenomena. However, prior literature either incorporates ethics into agent strategies or uses it for evaluation of agent behaviour. This work proposes a framework that models both, ethical decision making as well as evaluation using virtue ethics and utilitarianism. In an iteration, agents can use either the classical Continuous Prisoner's Dilemma or a new type of interaction called moral interaction, where agents donate or steal from other agents. We introduce moral interactions to (...)
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  35. Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents.Samuel Alexander - 2019 - Journal of Artificial General Intelligence 10 (1):24-45.
    Legg and Hutter, as well as subsequent authors, considered intelligent agents through the lens of interaction with reward-giving environments, attempting to assign numeric intelligence measures to such agents, with the guiding principle that a more intelligent agent should gain higher rewards from environments in some aggregate sense. In this paper, we consider a related question: rather than measure numeric intelligence of one Legg- Hutter agent, how can we compare the relative intelligence of two Legg-Hutter agents? We propose an elegant answer (...)
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  36. Legg-Hutter universal intelligence implies classical music is better than pop music for intellectual training.Samuel Alexander - 2019 - The Reasoner 13 (11):71-72.
    In their thought-provoking paper, Legg and Hutter consider a certain abstrac- tion of an intelligent agent, and define a universal intelligence measure, which assigns every such agent a numerical intelligence rating. We will briefly summarize Legg and Hutter’s paper, and then give a tongue-in-cheek argument that if one’s goal is to become more intelligent by cultivating music appreciation, then it is bet- ter to use classical music (such as Bach, Mozart, and Beethoven) than to use more recent pop music. The (...)
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  37. Robotic Nudges for Moral Improvement through Stoic Practice.Michał Klincewicz - 2019 - Techné: Research in Philosophy and Technology 23 (3):425-455.
    This paper offers a theoretical framework that can be used to derive viable engineering strategies for the design and development of robots that can nudge people towards moral improvement. The framework relies on research in developmental psychology and insights from Stoic ethics. Stoicism recommends contemplative practices that over time help one develop dispositions to behave in ways that improve the functioning of mechanisms that are constitutive of moral cognition. Robots can nudge individuals towards these practices and can therefore help develop (...)
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  38. A Non Monotonic Reasoning framework for Goal-Oriented Knowledge Adaptation.Antonio Lieto, Federico Perrone, Gian Luca Pozzato & Eleonora Chiodino - 2019 - In Paglieri (ed.), Proceedings of AISC 2019. Università degli Studi di Roma Tre. pp. 12-14.
    In this paper we present a framework for the dynamic and automatic generation of novel knowledge obtained through a process of commonsense reasoning based on typicality-based concept combination. We exploit a recently introduced extension of a Description Logic of typicality able to combine prototypical descriptions of concepts in order to generate new prototypical concepts and deal with problem like the PET FISH (Osherson and Smith, 1981; Lieto & Pozzato, 2019). Intuitively, in the context of our application of this logic, the (...)
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  39. A Description Logic Framework for Commonsense Conceptual Combination Integrating Typicality, Probabilities and Cognitive Heuristics.Antonio Lieto & Gian Luca Pozzato - 2019 - Journal of Experimental and Theoretical Artificial Intelligence:1-39.
    We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC + TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition. We first extend the logic of typicality ALC + TR by typicality inclusions of the (...)
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  40. Predicting Whether a Couple is Going to Get Divorced or Not Using Artificial Neural Networks.Ibrahim M. Nasser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (10):49-55.
    In this paper, an artificial neural network (ANN) model was developed and validated to predict whether a couple is going to get divorced or not. Prediction is done based on some questions that the couple answered, answers of those questions were used as the input to the ANN. The model went through multiple learning-validation cycles until it got 100% accuracy.
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  41. CesimaDigital: a tool for the History of Science.Odécio Souza - 2019 - Circumscribere: International Journal for the History of Science 24.
    This text is about the use of an Artificial Intelligence tool within the CESIMA's Digital Library.
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  42. (1 other version)Will Hominoids or Androids Destroy the Earth? —A Review of How to Create a Mind by Ray Kurzweil (2012) (review revised 2019).Michael Starks - 2019 - In Suicidal Utopian Delusions in the 21st Century -- Philosophy, Human Nature and the Collapse of Civilization-- Articles and Reviews 2006-2019 4th Edition Michael Starks. Las Vegas, NV USA: Reality Press. pp. 265-277.
    Some years ago, I reached the point where I can usually tell from the title of a book, or at least from the chapter titles, what kinds of philosophical mistakes will be made and how frequently. In the case of nominally scientific works these may be largely restricted to certain chapters which wax philosophical or try to draw general conclusions about the meaning or long term significance of the work. Normally however the scientific matters of fact are generously interlarded with (...)
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  43. Dreyfus on the “Fringe”: information processing, intelligent activity, and the future of thinking machines.Jeffrey White - 2019 - AI and Society 34 (2):301-312.
    From his preliminary analysis in 1965, Hubert Dreyfus projected a future much different than those with which his contemporaries were practically concerned, tempering their optimism in realizing something like human intelligence through conventional methods. At that time, he advised that there was nothing “directly” to be done toward machines with human-like intelligence, and that practical research should aim at a symbiosis between human beings and computers with computers doing what they do best, processing discrete symbols in formally structured problem domains. (...)
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  44. Epiphany Philosophers: Afterword.Rowan Williams - 2019 - Zygon 54 (4):1036-1044.
    Being a theist makes a difference, but not so much to what propositions we assent to, nor to an expanded ontology of spiritual entities. Rather, it is concerned with what commitments we enter into, and involves a participatory engagement with a broader reality then we might have supposed was possible. Embodied practices are a crucial part of the contemplative path, which draws on the wisdom of the body. This leads on to a “labor of culture.” Our present culture is not (...)
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  45. Study on effect of shared investing strategy on trust in AI.N. YokoiRyosuke & N. Kazuya - 2019 - Japanese Journal of Experimental 59 (1):46-50.
    This study examined the determinants of trust in artificial intelligence (AI) in the area of asset management. Many studies of risk perception have found that value similarity determines trust in risk managers. Some studies have demonstrated that value similarity also influences trust in AI. AI is currently employed in a diverse range of domains, including asset management. However, little is known about the factors that influence trust in asset management-related AI. We developed an investment game and examined whether shared investing (...)
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  46. CG-Art.Leonardo Arriagada - 2018 - In Richard Allen William, Olli Tapio Leino, Malina Siu & Sureshika Piyasena (eds.), Art Machines: International Symposium on Computational Media Art Proceedings. City University of Hong Kong. pp. 20-24.
    This aesthetic discussion examines in a philosophical-scientific way the relationship between computation and artistic creativity. Currently, there is criticism of the idea that an algorithm can be artistically creative. There are few exponents of the idea that computer-generated art (CG-Art) meets the definition of creativity proposed by Margaret Boden (2011): “the ability to come up with ideas or artifacts that are new, surprising, and valuable.” Moreover, it has been pointed out that CG-Art is not fundamentally art, because art is considered (...)
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  47. Heterogeneous Proxytypes Extended: Integrating Theory-like Representations and Mechanisms with Prototypes and Exemplars.Antonio Lieto - 2018 - In Advances in Intelligent Systems and Computing, Springer. Springer.
    The paper introduces an extension of the proposal according to which conceptual representations in cognitive agents should be intended as heterogeneous proxytypes. The main contribution of this paper is in that it details how to reconcile, under a heterogeneous representational perspective, different theories of typicality about conceptual representation and reasoning. In particular, it provides a novel theoretical hypothesis - as well as a novel categorization algorithm called DELTA - showing how to integrate the representational and reasoning assumptions of the theory-theory (...)
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  48. AISC 17 Talk: The Explanatory Problems of Deep Learning in Artificial Intelligence and Computational Cognitive Science: Two Possible Research Agendas.Antonio Lieto - 2018 - In Proceedings of AISC 2017.
    Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...)
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  49. Artificial intelligence in health care: enabling informed care.Tarassenko Lionel & Watkinson Peter - 2018 - The Lancet 1 (1):21-24.
    We read with interest the Lancet Editorial on artificial intelligence (AI) in health care (Dec 23, 2017, p 2739).1 Deep learning as a form of AI risks being overhyped. Deep neural networks contain multiple layers of nodes connected by adjustable weights. Learning occurs by adjusting these weights until the desired input-to-output function is achieved.2 With many millions of weights, huge amounts of data are required for learning, a process facilitated by recent increases in computational power. However, the learning algorithm, known (...)
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  50. The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI.Fernando Martínez-Plumed, Bao Sheng Loe, Peter Flach, Sean O. O. HEigeartaigh, Karina Vold & José Hernández-Orallo - 2018 - In Fernando Martínez-Plumed, Bao Sheng Loe, Peter Flach, Sean O. O. HEigeartaigh, Karina Vold & José Hernández-Orallo (eds.), Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence Evolution of the contours of AI. pp. 5180-5187.
    We present nine facets for the analysis of the past and future evolution of AI. Each facet has also a set of edges that can summarise different trends and contours in AI. With them, we first conduct a quantitative analysis using the information from two decades of AAAI/IJCAI conferences and around 50 years of documents from AI topics, an official database from the AAAI, illustrated by several plots. We then perform a qualitative analysis using the facets and edges, locating AI (...)
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